Highly discriminative and adaptive feature extraction method based on NMF-MFCC for event recognition of Φ-OTDR

  • Yi Huang
  • , Jingyi Dai
  • , Wei Shen
  • , Xiaofeng Chen
  • , Chengyong Hu
  • , Chuanlu Deng
  • , Lin Chen
  • , Xiaobei Zhang
  • , Wei Jin
  • , Jianming Tang
  • , Tingyun Wang

Research output: Contribution to journalArticlepeer-review

26 Downloads (Pure)

Abstract

To enhance the capability of phase-sensitive optical time domain reflectometers (Φ-OTDR) to recognize disturbance events, an improved adaptive feature extraction method based on NMF-MFCC is proposed, which replaces the fixed filter bank used in the traditional method to extract the mel-frequency cepstral coefficient (MFCC) features by a spectral structure obtained from the Φ-OTDR signal spectrum using nonnegative matrix factorization (NMF). Three typical events on fences are set as recognition targets in our experiments, and the results show that the NMF-MFCC features have higher distinguishability, with the corresponding recognition accuracy reaching 98.47%, which is 7% higher than that using the traditional MFCC features.

Original languageEnglish
Pages (from-to)9326-9333
Number of pages8
JournalApplied Optics
Volume62
Issue number35
Early online date2 Dec 2023
DOIs
Publication statusPublished - 10 Dec 2023

Fingerprint

Dive into the research topics of 'Highly discriminative and adaptive feature extraction method based on NMF-MFCC for event recognition of Φ-OTDR'. Together they form a unique fingerprint.

Cite this